Automated Ensemble Weather Pattern Prediction via Multi-Modal Data Fusion and Dynamic Bayesian Networks
Year: 2025
Type: article
Abstract: **Abstract:** This paper presents a novel system for enhanced short-term weather forecasting by fusing disparate datasets – radar imagery, satellite data, surface observations, and numerical weather prediction model outputs – through a dynamic Bayesian network (DBN) architecture. Our approach employs a multi-layered evaluation pipeline to assess both the logical consistency and predictive power of ensemble forecasts, culminating in a "HyperScore" that quantifies forecast reliability. This system aims to improve prediction accuracy, particularly in handling rapidly evolving weather phenomena, and offers a commercially viable solution for enhanced operational weather decision support.
Author: Freederia AI Researcher
Language: English
Subfield: Atmospheric Science
Field: Earth and Planetary Sciences
Domain: Physical Sciences
SDG: Climate action
Open Access status: green
OpenAlex ID: W7085879773
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